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Background <p>China’s aging population and declining birth rates create urgent demand for elderly care infrastructure. Rural areas face dual challenges: over 100,000 vacant schools from declining enrollment and elderly care facilities meeting less than 30% of demand. This study develops and validates a comprehensive framework for assessing rural school-to-elderly care facility conversion feasibility.</p> Methods <p>An integrated computational-expert consensus framework was developed combining natural language processing with expert validation. SciBERT extracted candidate indicators from 89 academic articles, 25 policy documents, and 31 stakeholder interviews. Fifteen multidisciplinary experts validated indicators through two-round Fuzzy Delphi process using triangular fuzzy numbers. Consensus was assessed using Kendall’s coefficient of concordance with 80% acceptance threshold.</p> Results <p>The model achieved F1-score of 0.85, precision of 0.87, and recall of 0.83. Expert validation yielded high consensus (Kendall’s W=0.781, <i>p</i>&lt;0.001), producing 17 validated indicators across four dimensions: building conditions, functional conversion, environmental renovation, and socioeconomic factors. Policy support emerged as most critical (weight=0.0792), followed by resource utilization and catering function (both 0.0669). All indicators achieved consensus rates of 80-100%.</p> Conclusions <p>This validated framework integrates computational objectivity with expert knowledge for evaluating rural school conversion feasibility. It provides practical guidance for policymakers and developers to address rural elderly care shortages through sustainable infrastructure adaptation, applicable to aging societies globally.</p>

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Transforming vacant rural school buildings into age-friendly facilities under China’s aging and low-fertility context: a natural language processing–based evaluation framework

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年1月9日

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  • Quan Wen,
  • Mazran Ismail,
  • Muhammad Hafeez Abdul Nasir

摘要

Background

China’s aging population and declining birth rates create urgent demand for elderly care infrastructure. Rural areas face dual challenges: over 100,000 vacant schools from declining enrollment and elderly care facilities meeting less than 30% of demand. This study develops and validates a comprehensive framework for assessing rural school-to-elderly care facility conversion feasibility.

Methods

An integrated computational-expert consensus framework was developed combining natural language processing with expert validation. SciBERT extracted candidate indicators from 89 academic articles, 25 policy documents, and 31 stakeholder interviews. Fifteen multidisciplinary experts validated indicators through two-round Fuzzy Delphi process using triangular fuzzy numbers. Consensus was assessed using Kendall’s coefficient of concordance with 80% acceptance threshold.

Results

The model achieved F1-score of 0.85, precision of 0.87, and recall of 0.83. Expert validation yielded high consensus (Kendall’s W=0.781, p<0.001), producing 17 validated indicators across four dimensions: building conditions, functional conversion, environmental renovation, and socioeconomic factors. Policy support emerged as most critical (weight=0.0792), followed by resource utilization and catering function (both 0.0669). All indicators achieved consensus rates of 80-100%.

Conclusions

This validated framework integrates computational objectivity with expert knowledge for evaluating rural school conversion feasibility. It provides practical guidance for policymakers and developers to address rural elderly care shortages through sustainable infrastructure adaptation, applicable to aging societies globally.